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Kuang Liu

Publications and source records attributed to Kuang Liu.

14 recordsLinked to original sources

A plug-and-play superconducting quantum controller at millikelvin temperatures enables exceeding 99.9% average gate fidelity

The development of large-scale superconducting quantum computing requires efficient in-situ control methods that allow high-fidelity operations at millikelvin temperatures. Superconducting circuits based on Josephson junctions offer a promising solution due to their high speed, low power dissipation, and cryogenic nature. Here, we report a superconducting quantum controller that enables direct chip-to-chip interconnection with qubits at 10 mK and high-fidelity, all-digital manipulation. Randomized benchmarking reveals a uniformly high average Clifford fidelity of 99.9% with leakage to high energy levels on the order of $10^{-4}$, and an estimated average gate operation energy of 0.121 fJ, demonstrating the potential to resolve the control bottleneck in superconducting quantum computing.

quant-ph

Light Manipulation via Tunable Collective Quantum States in Waveguide-Coupled Bragg and Anti-Bragg Superatoms

A many-body quantum system which consists of collective quantum states, such as superradiant and subradiant states, behaves as a multi-level superatom in light-matter interaction. In this work, we experimentally study one-dimensional superatoms in waveguide quantum electrodynamics with a periodic array of superconducting artificial atoms. We engineer the periodic atomic array with two distinct nearest-neighbor spacings, i.e., $d$=$\lambda_0/2$ and $d$=$\lambda_0/4$, which correspond to Bragg and anti-Bragg scattering conditions, respectively. The system consists of eight atoms arranged to maintain these specific interatomic distances. By controlling atomic frequencies, we modify Bragg and anti-Bragg superatoms, resulting in distinctly different quantum optical phenomena, such as collectively induced transparency and a broad photonic bandgap. Moreover, due to strong waveguide-atom couplings in superconducting quantum circuits, efficient light manipulations are realized in small-size systems. Our work demonstrates tunable optical properties of Bragg and anti-Bragg superatoms, as well as their potential applications in quantum devices.

quant-ph

Single-flux-quantum-based Qubit Control with Tunable Driving Strength

Single-flux-quantum (SFQ) circuits have great potential in building cryogenic quantum-classical interfaces for scaling up superconducting quantum processors. SFQ-based quantum gates have been designed and realized. However, current control schemes are difficult to tune the driving strength to qubits, which restricts the gate length and usually induces leakage to unwanted levels. In this study, we design the scheme and corresponding pulse generator circuit to continuously adjust the driving strength by coupling SFQ pulses with variable intervals. This scheme not only provides a way to adjust the SFQ-based gate length, but also proposes the possibility to tune the driving strength envelope. Simulations show that our scheme can suppress leakage to unwanted levels and reduce the error of SFQ-based Clifford gates by more than an order of magnitude.

quant-ph

Quasiparticle Dynamics in Superconducting Quantum-Classical Hybrid Circuits

Single flux quantum (SFQ) circuitry is a promising candidate for a scalable and integratable cryogenic quantum control system. However, the operation of SFQ circuits introduces non-equilibrium quasiparticles (QPs), which are a significant source of qubit decoherence. In this study, we investigate QP behavior in a superconducting quantum-classical hybrid chip that comprises an SFQ circuit and a qubit circuit. By monitoring qubit relaxation time, we explore the dynamics of SFQ-circuit-induced QPs. Our findings reveal that the QP density near the qubit reaches its peak after several microseconds of SFQ circuit operation, which corresponds to the phonon-mediated propagation time of QPs in the hybrid circuits. This suggests that phonon-mediated propagation dominates the spreading of QPs in the hybrid circuits. Our results lay the foundation to suppress QP poisoning in quantum-classical hybrid systems.

quant-ph

Thin film aluminum nitride surface acoustic wave resonators for quantum acoustodynamics

The quantum excitations of macroscopic surface acoustic waves (SAWs) have been tailored to control, communicate and transduce stationary and flying quantum states. However, the limited lifetime of this hybrid quantum systems remains critical obstacles to extend their applications in quantum information processing. Here we present the potentials of thin film aluminum nitride to on-chip integrate phonons with superconducting qubits over previous bulk piezoelectric substrates. We have reported high-quality thin film GHz-SAW resonators with the highest internal quality factor Qi of 5 e4 at the single-phonon level. The internal loss of SAW resonators are systematically investigated with tuning the parameters of sample layout, power and temperature. Our results manifest that SAWs on piezoelectric films are readily integrable with standard fabrication of Josephson junction quantum circuits, and offer excellent acoustic platforms for the high-coherence quantum acoustodynamics architectures.

quant-ph

Multiscale Graph Neural Networks for Protein Residue Contact Map Prediction

Machine learning (ML) is revolutionizing protein structural analysis, including an important subproblem of predicting protein residue contact maps, i.e., which amino-acid residues are in close spatial proximity given the amino-acid sequence of a protein. Despite recent progresses in ML-based protein contact prediction, predicting contacts with a wide range of distances (commonly classified into short-, medium- and long-range contacts) remains a challenge. Here, we propose a multiscale graph neural network (GNN) based approach taking a cue from multiscale physics simulations, in which a standard pipeline involving a recurrent neural network (RNN) is augmented with three GNNs to refine predictive capability for short-, medium- and long-range residue contacts, respectively. Test results on the ProteinNet dataset show improved accuracy for contacts of all ranges using the proposed multiscale RNN+GNN approach over the conventional approach, including the most challenging case of long-range contact prediction.

q-bio.QM

Discrete Element Simulations and Machine Learning for Improving the Performance of Dry Catalyst Continuous Impregnation Processes

In this work, discrete element method (DEM) simulations coupled with machine learning are used to study the process of dry impregnation. Our results show that the particle bed contains two regimes. Regime 1 shows smaller inclination angles and a larger mass hold-up which implies more forces restricting the particle movement. Regime 2 reveals larger inclination angles and rotational speeds and a smaller mass holdup, which indicates a smaller bed height. Using Machine learning, we found a general function for the Relative Standard Deviation (RSD) as a function of time, angle of inclination and speed of rotation for both even and uneven flow rates for a full range of the parameters fed in the LASSO algorithm. Machine learning gives insight on both regimes and reveals that for low RPM and low angles, uneven spraying gives a lower RSD which is consistent with our observations of the DEM studies.

physics.app-ph

Dynamic nuclear structure emerges from chromatin crosslinks and motors

The cell nucleus houses the chromosomes, which are linked to a soft shell of lamin filaments. Experiments indicate that correlated chromosome dynamics and nuclear shape fluctuations arise from motor activity. To identify the physical mechanisms, we develop a model of an active, crosslinked Rouse chain bound to a polymeric shell. System-sized correlated motions occur but require both motor activity {\it and} crosslinks. Contractile motors, in particular, enhance chromosome dynamics by driving anomalous density fluctuations. Nuclear shape fluctuations depend on motor strength, crosslinking, and chromosome-lamina binding. Therefore, complex chromatin dynamics and nuclear shape emerge from a minimal, active chromosome-lamina system.

q-bio.SC

Sponge-like rigid structures in frictional granular packings

We show how rigidity emerges in experiments of sheared frictional granular materials by using generalizations of two methods for identifying rigid structures. Both approaches, the force-based dynamical matrix and the topology-based rigidity percolation, agree with each other and identify similar rigid structures. As the system becomes jammed, at a contact number of $z=2.4\pm 0.1$, a rigid backbone interspersed with floppy, particle-filled holes of a broad range of sizes emerges, creating a sponge-like morphology. We also find that the pressure within rigid structures always exceeds the pressure outside the rigid structures, i.e. that the backbone is load-bearing. These findings shows that it is necessary to go beyond mean-field theory to capture the physics of frictional jamming and also suggests that mechanical stability arises through arch structures and hinges at the mesoscale.

cond-mat.soft

Domain-Specific Compilers for Dynamic Simulations of Quantum Materials on Quantum Computers

Simulation of the dynamics of quantum materials is emerging as a promising scientific application for noisy intermediate-scale quantum (NISQ) computers. Due to their high gate-error rates and short decoherence times, however, NISQ computers can only produce high-fidelity results for those quantum circuits smaller than some given circuit size. Dynamic simulations, therefore, pose a challenge as current algorithms produce circuits that grow in size with each subsequent time-step of the simulation. This underscores the crucial role of quantum circuit compilers to produce executable quantum circuits of minimal size, thereby maximizing the range of physical phenomena that can be studied within the NISQ fidelity budget. Here, we present two domain-specific quantum circuit compilers for the Rigetti and IBM quantum computers, specifically designed to compile circuits simulating dynamics under a special class of time-dependent Hamiltonians. The compilers outperform state-of-the-art general-purpose compilers in terms of circuit size reduction by around 25-30% as well as wall-clock compilation time by around 40% (dependent on system size and simulation time-step). Drawing on heuristic techniques commonly used in artificial intelligence, both compilers scale well with simulation time-step and system size. Code for both compilers is included to enhance the results of dynamic simulations for future researchers. We anticipate that our domain-specific compilers will enable dynamic simulations of quantum materials on near-future NISQ computers that would not otherwise be possible with general-purpose compilers.

quant-ph

Towards Dynamic Simulations of Materials on Quantum Computers

A highly anticipated application for quantum computers is as a universal simulator of quantum many-body systems, as was conjectured by Richard Feynman in the 1980s. The last decade has witnessed the growing success of quantum computing for simulating static properties of quantum systems, i.e., the ground state energy of small molecules. However, it remains a challenge to simulate quantum many-body dynamics on current-to-near-future noisy intermediate-scale quantum computers. Here, we demonstrate successful simulation of nontrivial quantum dynamics on IBM's Q16 Melbourne quantum processor and Rigetti's Aspen quantum processor; namely, ultrafast control of emergent magnetism by THz radiation in an atomically-thin two-dimensional material. The full code and step-by-step tutorials for performing such simulations are included to lower the barrier to access for future research on these two quantum computers. As such, this work lays a foundation for the promising study of a wide variety of quantum dynamics on near-future quantum computers, including dynamic localization of Floquet states and topological protection of qubits in noisy environments.

quant-ph

Rigidity percolation control of the brittle-ductile transition in disordered networks

In ordinary solids, material disorder is known to increase the size of the process zone in which stress concentrates at the crack tip, causing a transition from localized to diffuse failure. Here, we report experiments on disordered 2D lattices, derived from frictional particle packings, in which the mean coordination number $\langle z \rangle$ of the underlying network provides a similar control. Our experiments show that tuning the connectivity of the network provides access to a range of behaviors from brittle to ductile failure. We elucidate the cooperative origins of this transition using a frictional pebble game algorithm on the original, intact lattices. We find that the transition corresponds to the isostatic value $\langle z \rangle = 3$ in the large-friction limit, with brittle failure occurring for structures vertically spanned by a rigid cluster, and ductile failure for floppy networks containing nonspanning rigid clusters. Furthermore, we find that individual failure events typically occur within the floppy regions separated by the rigid clusters.

cond-mat.soft

Frictional rigidity percolation and minimal rigidity proliferation: From a new universality class to superuniversality

We introduce two new concepts, frictional rigidity percolation and minimal rigidity proliferation, to help identify the nature of the frictional jamming transition as well as significantly broaden the scope of rigidity percolation. For frictional rigidity percolation, we construct rigid clusters in two different lattice models using a $(3,3)$ pebble game, while taking into account contacts below and at the Coulomb threshold. The first lattice is a honeycomb lattice with next-nearest neighbors, the second, a hierarchical lattice. For both, we generally find a continuous rigidity transition. Our numerical results suggest that, for the honeycomb lattice, the exponents associated with the transition found with the frictional $(3,3)$ pebble game are distinct from those of a central-force $(2,3)$ pebble game. We propose that localized motifs, such as hinges, connecting rigid clusters that are allowed only with friction could give rise to this new frictional universality class. However, the closeness of the order parameter exponent between the two cases hints at potential superuniversality. To explore this possibility, we construct a bespoke cluster generating algorithm invoking generalized Henneberg moves, dubbed minimal rigidity proliferation. The minimally rigid clusters the algorithm generates appear to be in the same universality class as connectivity percolation, suggesting superuniversality between all three types of transitions. Finally, the hierarchical lattice is analytically tractable and we find that the exponents depend both on the type of force and on the fraction of contacts at the Coulomb threshold. These combined results allow us to compare two universality classes on the same lattice via rigid clusters for the first time to highlight unifying and distinguishing concepts within the set of all possible rigidity transitions in disordered systems.

cond-mat.soft

Fully Coupled Electromechanical Elastodynamic Model for Guided Wave Propagation Analysis

Physics-based computational models play a key role in the study of wave propagation for structural health monitoring (SHM) and the development of improved damage detection methodologies. Due to the complex nature of guided waves, accurate and efficient computation tools are necessary to investigate the mechanisms responsible for dispersion, coupling, and interaction with damage. In this paper, a fully coupled electromechanical elastodynamic model for wave propagation in a heterogeneous, anisotropic material system is developed. The final framework provides the full three dimensional displacement and electrical potential fields for arbitrary plate and transducer geometries and excitation waveform and frequency. The model is validated theoretically and proven computationally efficient. Studies are performed with surface bonded piezoelectric sensors to gain insight into the physics of experimental techniques used for SHM. Collocated actuation of the fundamental Lamb wave modes is modeled over a range of frequencies to demonstrate mode tuning capabilities. The displacement of the sensing surface is compared to the piezoelectric sensor electric potential to investigate the relationship between plate displacement and sensor voltage output. Since many studies, including the ones investigated in this paper, are difficult to perform experimentally, the developed model provides a valuable tool for the improvement of SHM techniques.

physics.class-ph